A data mining approach to discover unusual folding regions in genome sequences

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Nov 20, 2013 (3 years and 6 months ago)

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A data mining approach to discover
unusual folding regions in genome
sequences

Shu
-
Yun Le, Wei
-
min Liu, and Jacob V.Maizel Jr.

Knowledge
-
Based System, No.15, pp243
-
250, 2002

1.

Introduction

Numerous experiment and analysis of RNA structure have
revealed that
the local distinct structure closely correlates with the
biological function. In this study,we present a data mining
approach to discover such unusual folding regions(UFRs) in
genome sequences.

2.

Mathematical Background




UFR in an RNA sequence are assessed b
y the two scores ,
significant score(SIGSCR) , and stability score(STBSCR).


SIGSCR=
r
r
std
E
E
/
)
(



STBSCR=
w
w
std
E
E
/
)
(





Lineary transformed non
-
central Student`s t
distribution(LTNSTD)




(1)


(2)



Let the data, SIGSCR & STBSCR be
}
1
,
{
n
i
y
i






(3)


(4)


(5)

3.

Procedure



(1)

first step : computing SI
GSCR & STBSCR


(2)

second step : deriving a LTNSTD for SIGSCR & STBSCR


(3)

third srep :
discoveries

of UFRs









4.Result





Created by :
Hung
-
Wei Huang

Date : Oct. 25, 2002